All machines and physical structures produce vibrations and resonances of various kinds, some of which may be characteristic of normal operation and others of which may indicate off-normal conditions, unusual wear, incipient failure, or other problems. In the field of predictive maintenance, the detection of vibrational signatures is a key element of the diagnostic process in which the goal is to identify and remedy incipient problems before a more serious event such as breakdown, failure, or service interruption occurs. Often it is desirable to visually inspect a mechanical component to determine if physical damage is present. This can be done by stopping the motion and performing a physical inspection; however, shutting equipment down and interrupting its operation to determine the presence of a fault condition or the extent of damage is undesirable.
One method that has been used to perform visual inspections while a machine is still in operation is by means of a stroboscope. This instrument flashes a high intensity light at user selected frequencies. When the frequency of flashing is exactly at the frequency of interest, the motion of the moving component appears to freeze. When the frequency of flashing differs slightly from the frequency of motion, then the component will appear to turn very slowly in a forward or backward direction. However, the stroboscope is limited by the perception of the human eye. Very slow frequencies are too intermittent to give a perception of stopping the motion because there is too large of a delay between the flashes. At very high frequencies, the flashes are so close together that the eye only sees a steady source of light and this prevents the motion from appearing to be frozen.
Since digitally captured data can be played back at any frequency which suits the perception capabilities of the human eye, it allows very slow or very fast frequencies to be rendered in a visually perceptive manner. Additionally, by selecting sample rates which are not synchronous with the frequency of interest, reconstructed video output can render what appears to be a very high angular resolution of the component which would normally only be achievable by cameras with a very high frame rate. When the frequency of interest is too high to be adequately characterized satisfactorily by the frame rate of the camera, the digital phenomena of aliasing still allows a video stream to be constructed that provides a very high detail examination of the component as it progresses through its cycle.
Also, whereas a stroboscope depends on the skill of the user to locate the correct frequency of motion and then to make the component turn slowly, by comparison a more preferred video system would only require the user to identify the object of interest by making a graphical selection from a single frame of the video. The system could automatically, and without variability that depends on user actions, determine the frequency of motion, calculate an optimum frame rate, set the shutter rate to the maximum or equivalently sets the brightness control or exposure time to the minimum value or sufficiently small enough value, collect the needed data, and reconstruct an output video which would enable a visual inspection of the component with very high resolution. Current embodiments are directed to providing this advantage with digital photography and video.
U.S. Pub. No. 2016/0217587 titled “Apparatus and Method for Analyzing Periodic Motions in Machinery” (Hay, Jeffrey R.; published Jul. 28, 2016), and later issued as U.S. Pat. No. 10,459,615, the contents of which are incorporated by reference herein, describes multiple embodiments that provide a non-contact vibration analysis system for machinery and structures. The embodiments described therein provide a number of features and advantages, not least among them is a flexible predictive maintenance tool that use vibrations to diagnose fault conditions using a video-based tool for evaluating the dynamic motions in machinery without the need for edge visualization or identification of other specific objects in the scene.
For example, the descriptions contained in US Pub. No. 2016/0217587, titled “Apparatus and Method for Analyzing Periodic Motions in Machinery” (Hay, Jeffrey R.; published Jul. 28, 2016, Application No. 14/757,245 filed Dec. 9, 2015), the contents of which are fully incorporated herein by reference, refer to multiple embodiments of a system for analyzing periodic (i.e., repeated) motions in machinery. This system comprises one or more video acquisition devices, such as but not limited to one or more video cameras, webcams, or digital cameras integral in cells phones, positioned at a selected distance from a machine component or physical structure (i.e., object). This video acquisition device will be positioned with an unobstructed view of a selected portion of the object to obtain a video feed. This video, as is the case with the videos described in the present disclosure, is divisible into individual image frames, with each frame showing a static image of a scene, and with each frame being divisible into a plurality of pixels. This system further comprises a data analysis system, including a processor and memory to analyze the video file, such as by measuring a value which is characteristic of the object's physical movement over time to thereby determine the periodicity of that movement. The system in U.S. Pub. No. 2016/0217587 further comprises a data storage system to archive the video for later retrieval and comparison of the images and the measurements from the video, the image frames, or an enhanced version of the video. This comparison is the foundation for providing determining changes in the object's movement data, which may be indicative of mechanical anomalies.
In any such endeavor, however, it is important to understand that certain movements of interest by an object happen at such a high frequency as to not be discernible by a human observer with the naked eye or a person watching a video obtained from an actual scene with moving parts. For example, a vibration occurring in a machine component at 60 Hz, as an example, may need to be slowed down on video to discern what is actually happening with the component. With appropriate program instructions, the inventive system and methods disclosed herein may then be configured to compare spectrums for the two videos to see what peaks are shared. The shared peaks could be counted as normal behavior, whereas the peaks that are not common to the two spectra may be identified as changes in the vibration behavior, which may be associated with deteriorating conditions. Such approaches make the practice of the present embodiments more efficient and less prone to guess work.
Often, the conditions that indicate a problem or need for intervention that are captured by the video acquisition device are subtle ones that occur simultaneously with normal movements (i.e., substantially as designed and not a root cause or indicator of ongoing or future problems) of a machine or component. Consider a shaft that rotates as a normal movement, yet also has a vibration undiscernible to the naked eye that is accompanying this rotational movement. In this sense, the normal rotation of the shaft is not of concern, but one investigating the condition of the shaft would be interested in waveforms of each rotation from which the vibrational anomaly can be determined. Examples where visual inspection might be very helpful would include damaged or dirty blades, bent, bowed, or damaged shafts, and looseness or rubs. Accordingly, as discussed herein, the present embodiments efficiently and reliably achieve the objective of verifying specific fault conditions clearly based on a visual inspection based on recorded images acquired while the component is in normal operation.